# compare instore to online ratio and potential for the online shift before and after covid
# transactions_ratio >> on a given day, ___ times more people shop instores rather than online (2 line graph showing the trend before and after covid and online vs instore trends)
# walmart_instore_sum <-
# walmart_instore %>%
# mutate(month = paste0(substr(date,1,4),"-",substr(date,6,7))) %>%
# group_by(month) %>%
# summarize(
# mean=mean(as.numeric(total_spent)),
# sum=sum(as.numeric(total_spent)),
# avg_transactions=mean(as.numeric(transaction_counts)),
# transactions=sum(as.numeric(transaction_counts)))
#
# walmart_sum <-
# walmart_online %>%
# mutate(month = paste0(substr(date,1,4),"-",substr(date,6,7)))%>%
# group_by(month) %>%
# summarize(
# mean=mean(as.numeric(total_spent)),
# sum=sum(as.numeric(total_spent)),
# avg_transactions=mean(as.numeric(transaction_counts)),
# transactions=sum(as.numeric(transaction_counts))) %>%
# left_join(walmart_instore_sum,by="month",suffix=c("_online","_instore"))
#
# walmart_melt <-
# walmart_sum %>%
# tail(12) %>%
# mutate(transactions_ratio_instore=(avg_transactions_instore)/(sum(walmart_sum[, 'avg_transactions_instore']))) %>%
# mutate(transactions_ratio_online=(avg_transactions_online)/(sum(walmart_sum[, 'avg_transactions_online']))) %>%
# dplyr::select(month,transactions_ratio_instore,transactions_ratio_online) %>%
# melt(id=c("month"))
# saveRDS(walmart_melt,"walmart_transactions.rds")
walmart_melt <- readRDS("baymap/walmart_transactions.rds")
ggplot(walmart_melt,aes(x=month,y=value,color=variable,group=variable)) +
geom_line(size=1.5) +
labs(y= "Transactions Ratio", x = "Year-Month", color="Legend") +
theme(axis.text.y =element_blank(),
axis.ticks.y=element_blank())

pal <- sequential_hcl("red-blue",n=3,rev=T)
col <- colorNumeric(pal,domain=spending_brand_sum$transactions_avg)
fp <- leaflet() %>%
addProviderTiles(providers$CartoDB.VoyagerLabelsUnder, group = "Default") %>%
addTiles(urlTemplate = mapbox_sat, attribution = mapbox_satAtt, group = "Satellite") %>%
addPolygons(
data = spending_brand_sum,
color = col(spending_brand_sum$transactions_avg),
weight=1,
popup = paste0(
"<strong>",spending_brand_sum$zip,"</strong><br>",
spending_brand_sum$transactions_avg),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto"),
group = "All"
) %>%
addPolygons(
data = spending_brand_sum_top5,
weight=2,
color = "red",
popup = paste0(
"<strong>",spending_brand_sum_top5$zip,"</strong><br>",
spending_brand_sum_top5$transactions_avg),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto"),
group = "Top 5"
) %>%
addPolygons(
data = spending_brand_sum_top10,
color = "red",
weight=2,
popup = paste0(
"<strong>",spending_brand_sum_top10$zip,"</strong><br>",
spending_brand_sum_top10$transactions_avg),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto"),
group = "Top 10"
) %>%
addLegend(
position = 'bottomleft',
values = spending_brand_sum$transactions_avg,
pal = col,
title='Avg Daily Walmart Transactions'
) %>%
addLayersControl(
baseGroups = c("Default","Satellite"),
overlayGroups = c("All","Top 5","Top 10")
) %>%
hideGroup(c("Top 5","Top 10"))
fp